Replikins Analysis

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Prediction of specific virus outbreaks made from the increased concentration of a new class of virus genomic peptides, replikins.

Samuel Bogoch* and Elenore S. Bogoch**

Abstract

Advance warning of pathogen outbreaks has not been possible heretofore. A new class of genomic peptides associated with rapid replication was discovered and named replikins.

Software was designed to analyze replikins quantitatively. Replikin concentration changes were measured annually prior to, and “real time” every few days during, the 2009 H1N1 influenza pandemic. Replikins were seen by both linear sequence representation and three-dimensional Xray diffraction, and found to expand on the virus hemagglutinin surface prior to and during the H1N1 pandemic.

A highly significant increased concentration of virus replikins was found a) retrospectively in three pandemics from 1918 to 1999 (14,227 sequences)(p<0.001), and b) prospectively before the H1N1 2009 pandemic (12,806 sequences) (in the hemagglutinin gene (N=8,046), p values by t-test = 1/10130, by linear regression = 1/1024 and 1/1029, by Spearman correlation < 2/1016, by
Wilcoxon rank sum<1/1016, by multiple regression adjusting for correlation between consecutive years = 2/1022. Rising replikin concentration in H1N1 from 2006 to 2008, predicted one year in advance the H1N1 outbreak of 2009; and in H5N1, predicted the lethal outbreaks of H5N1 1997-2010.

The possible combination of influenza strains H1N1 (high infectivity) and H5N1 (high lethality) is a matter of global concern (1,2). The risk of a combined H1N1 (high infectivity) - H5N1 (high lethality) outbreak may have increased because first, the Replikin Counts of the two virus strains have risen simultaneously, not seen reviously; second, the rise is to the highest levels recorded since 1918 for H1N1, in Mexico (16.7), and since 1957 for H5N1, in Egypt (23.3); and third, clinical outbreaks of each strain are occurring in 2011. These simultaneous conditions may increase the risk that the two virus strains might come into contact with each other more frequently, facilitating transfer of genomic material to form a hybrid.

*Senior Scholar, Boston University School of Medicine
**Director, Foundation for Research on the Nervous System (FRNS), 36 The Fenway, Boston MA 02215

Introduction

No structures of infectious organisms have been described to date which correlate quantitatively and temporally with epidemic outbreaks, course, and lethality, and permit early or advance warning of such outbreaks. Replikins are genomic structures related to rapid replication defined by the authors’ algorithm: peptides 7 to 50 amino acids long, containing two or more lysines, six to ten amino acids apart, at least one histidine, and a lysine concentration of 6% or more (8).

Replikins are the first reported conserved virus structures whose increasing concentration correlates quantitatively with, and predict, strain-specific virus outbreaks.

As observed in the 2009 H1N1 pandemic, advanced Replikins warning was published one year in advance, in April 2008 (12). The outbreak occurred in April 2009. Because of the time taken to produce vaccine, vaccine was not available when the brunt of the pandemic struck in April 2009. Only 20% of the world’s population at risk had vaccine available, and that was eight months after the outbreak, when the virus Replikin Count had already indicated that the lethal aspects of the pandemic would soon be over except for a brief recurrence in December 2010, also predicted (Figure 1a). Fortunately, so far, the H1N1 pandemic has been less severe than the three pandemics in the last century. The 2011 outbreaks have begun for both H1N1 and H5N1.

Initial ‘scout‘ virus outbreaks of H1N1 have occurred, again in Mexico, with Replikin Counts of the Infectivity Gene up to a record 16.7 (see below) and a human mortality rate of 10.7% (2); and
outbreaks of H5N1 in Egypt, better established, have begun with a current cumulative mortality rate of from 34.7% (3,4) to 37.8% (5). It is generally agreed that new approaches are required for the control of acute emergent diseases (6.7). Five year plans with the hope to have a vaccine available in five years may not be relevant to the current threat (24).

The benefits of having more time to prepare for and to respond to acute lethal environmental events has been demonstrated in satellite warnings for hurricanes. The consequences of having
little or no advance warning have been recently demonstrated in earthquake-tsunamis and in the 2009 H1N1 influenza pandemic. To date there have been no reliable technologies to predict emergence of specific virus strains. The only global surveillance available is post outbreak and based solely on epidemiological data (1). Acute emergent infectious diseases coupled with current global travel pose challenges to timely implementation of public health measures such as tracking and isolation of cases, and the design, testing and distribution of specific effective vaccines and therapeutics to the world’s population.

Methods

Software based on the authors’ algorithm (9) first identified and then counted the replikin peptides in each genomic sequence (Replikin Count = number of replikins per 100 amino acids). For each group of specimens’ replikins, the mean and standard deviation of the mean (SD) were calculated and compared over the past 93 years. Highly statistically significant increases and decreases were examined, for example by strain, host, country, history, year, month or week; by substitution, morbidity, and lethality.

The terms ‘increase’ and ‘decrease’ of Replikin Counts were used only when the p level was less than 0.001. Counts in H1N1, H5N1 and other influenza strains were each monitored separately, retrospectively from 1918 to 1999, and prospectively from 2000-2011 for all countries reporting to Pubmed. During outbreaks, Replikin Counts were compared to Counts for the same strain in non-outbreak (‘resting’) time periods. Statistical analyses of rate of change, trend, pattern, and growth models in the evolution of each
virus strain were initiated. Replikin genes were isolated in silico by scanning and identifying those areas of the virus genome which had the highest concentration of replikins. When the eight H5N1 genomic
areas were examined year by year, gene areas were found which became upregulated when associated with particular outbreaks. When the upregulation was found to be associated with high infectivity (morbidity over time period), the high Count area was named Replikin Infectivity Gene. When a high Count area in a sequence was found to be associated with high mortality rates, the high Count area was named Replikin Lethality Gene. The Replikin Count of these two genes in the H1N1 virus were determined annually from 2001 to 2008 before the pandemic, then during the pandemic ‘real-time’ every Precedings : doi:10.1038/npre.2011.6279.1 : Posted 22 Aug 2011

few days, then weekly, from April 2009 to February 2011. When Replikin Counts exceeded 5 per 100 amino acids, stacking was sought and found. Counts were expressed in two ways: 1) for the entire gene, e.g. for the entire hemagglutinin gene in H1N1 (as employed in Figures 1-4); and 2) for the highest concentration of Replikins within each infectivity or lethality gene, which was designated the Replikin Peak Gene (Figures 4 and 5). Human morbidity and mortality rates data during particular time periods
(CDC and WHO)(10,11) were compared with Replikin Counts.

Replikin peptides were visualized by two means: a) by linear display of sequences of contiguous numbered amino acids in the primary structure and b) by X-ray diffraction analysis of the 3-dimensional folded structure.

RESULTS CONTINUED:

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